Stanford engineers have somehow taken the iconic DeLorean and made it even cooler, by teaching the vehicle self-driving capabilities to flawlessly drift through a racecourse.
The DeLorean, which left its mark on the movie industry through the Back to the Future series, is now also turning heads in the self-driving technology space. Appropriately, Stanford’s version of the sleek vehicle is named MARTY, after Michael J. Fox’s character Marty McFly.
Jonathan Goh, a mechanical engineering doctorate graduate from Stanford, led a team from the university’s Dynamic Design Lab to create MARTY, a 1981 DeLorean that was converted into an all-electric, self-driving, drifting machine. The car features custom suspension and bigger brakes, and is equipped with onboard computers and a pair of GPS antennae for location tracking.
MARTY first drifted, which is the style of driving where the car keeps moving forward while pointed sideways, four years ago. Goh and his team have since been busy in preparing the DeLorean to drift through a driving course. All their efforts paid off perfectly, as MARTY completed the course without toppling over a single cone.
The video of MARTY’s impressive feat showed a flawless run through the 1-kilometer obstacle course, dubbed “MARTYkhana.” There were two passengers, but neither one needed to take control at any point as the DeLorean exercised extreme precision in turning, stepping on the throttle, and applying brakes.
While most of the self-driving vehicles that are currently on the road were designed for the simple, everyday situations that drivers experience, lead project engineer Chris Gerdes said that MARTY is the product of a goal to develop automated cars that will be capable of handling emergency maneuvers or slippery roads when covered with ice or snow.
“We’d like to develop automated vehicles that can use all of the friction between the tire and the road to get the car out of harm’s way. We want the car to be able to avoid any accident that’s avoidable within the laws of physics,” said Gerdes.
According to Goh, drifting generates extreme examples of driving physics that may not be obtained in other scenarios. “If we can conquer how to safely control the car in the most stable and the most unstable scenarios, it becomes easier to connect all the dots in between.”
